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Economic dispatch using particle swarm optimization: A review

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  • Mahor, Amita
  • Prasad, Vishnu
  • Rangnekar, Saroj

Abstract

Electrical power industry restructuring has created highly vibrant and competitive market that altered many aspects of the power industry. In this changed scenario, scarcity of energy resources, increasing power generation cost, environment concern, ever growing demand for electrical energy necessitate optimal economic dispatch. Practical economic dispatch (ED) problems have nonlinear, non-convex type objective function with intense equality and inequality constraints. The conventional optimization methods are not able to solve such problems as due to local optimum solution convergence. Meta-heuristic optimization techniques especially particle swarm optimization (PSO) has gained an incredible recognition as the solution algorithm for such type of ED problems in last decade. The application of PSO in ED problem, which is considered as one of the most complex optimization problem has been summarized in present paper.

Suggested Citation

  • Mahor, Amita & Prasad, Vishnu & Rangnekar, Saroj, 2009. "Economic dispatch using particle swarm optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2134-2141, October.
    • Handle: RePEc:eee:rensus:v:13:y:2009:i:8:p:2134-2141
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    1. Smarajit Ghosh & Manvir Kaur & Suman Bhullar & Vinod Karar, 2019. "Hybrid ABC-BAT for Solving Short-Term Hydrothermal Scheduling Problems," Energies, MDPI, vol. 12(3), pages 1-15, February.
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    4. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    5. Lai, Wenhao & Zheng, Xiaoliang & Song, Qi & Hu, Feng & Tao, Qiong & Chen, Hualiang, 2022. "Multi-objective membrane search algorithm: A new solution for economic emission dispatch," Applied Energy, Elsevier, vol. 326(C).
    6. Meng, Anbo & Hu, Hanwu & Yin, Hao & Peng, Xiangang & Guo, Zhuangzhi, 2015. "Crisscross optimization algorithm for large-scale dynamic economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 93(P2), pages 2175-2190.
    7. Santhosh, Apoorva & Farid, Amro M. & Youcef-Toumi, Kamal, 2014. "Real-time economic dispatch for the supply side of the energy-water nexus," Applied Energy, Elsevier, vol. 122(C), pages 42-52.
    8. Shehab Al-Sakkaf & Mahmoud Kassas & Muhammad Khalid & Mohammad A. Abido, 2019. "An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch," Energies, MDPI, vol. 12(8), pages 1-25, April.
    9. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher, 2012. "Multi-operation management of a typical micro-grids using Particle Swarm Optimization: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1268-1281.
    10. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    11. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    12. Wang, K.Y. & Luo, X.J. & Wu, L. & Liu, X.C., 2013. "Optimal coordination of wind-hydro-thermal based on water complementing wind," Renewable Energy, Elsevier, vol. 60(C), pages 169-178.
    13. Fatma Yaprakdal & Mustafa Baysal & Amjad Anvari-Moghaddam, 2019. "Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources," Energies, MDPI, vol. 12(10), pages 1-17, May.
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    15. Iqbal, M. & Azam, M. & Naeem, M. & Khwaja, A.S. & Anpalagan, A., 2014. "Optimization classification, algorithms and tools for renewable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 640-654.
    16. Al-Sulttani, Ali O. & Ahsan, Amimul & Hanoon, Ammar N. & Rahman, A. & Daud, N.N.N. & Idrus, S., 2017. "Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique," Applied Energy, Elsevier, vol. 203(C), pages 280-303.
    17. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
    18. Karar Mahmoud & Mohamed Abdel-Nasser & Eman Mustafa & Ziad M. Ali, 2020. "Improved Salp–Swarm Optimizer and Accurate Forecasting Model for Dynamic Economic Dispatch in Sustainable Power Systems," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    19. Gerardo J. Osório & Miadreza Shafie-khah & Juan M. Lujano-Rojas & João P. S. Catalão, 2018. "Scheduling Model for Renewable Energy Sources Integration in an Insular Power System," Energies, MDPI, vol. 11(1), pages 1-16, January.
    20. Shahbaz Hussain & Mohammed Al-Hitmi & Salman Khaliq & Asif Hussain & Muhammad Asghar Saqib, 2019. "Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant," Energies, MDPI, vol. 12(11), pages 1-15, May.
    21. Kheshti, Mostafa & Ding, Lei & Ma, Shicong & Zhao, Bing, 2018. "Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems," Renewable Energy, Elsevier, vol. 125(C), pages 1021-1037.
    22. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "Economic dispatch of multiple energy carriers," Energy, Elsevier, vol. 138(C), pages 861-872.
    23. Upadhyay, Subho & Sharma, M.P., 2014. "A review on configurations, control and sizing methodologies of hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 47-63.
    24. Pezzini, Paola & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Optimization techniques to improve energy efficiency in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 2028-2041, May.
    25. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & B. Gharehpetian, G., 2017. "Short-term scheduling of hydro-based power plants considering application of heuristic algorithms: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 116-129.

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